Reduction of lymph tissue false positives in pulmonary embolism detection

Bernard Ghanem; Jianming Liang; Jinbo Bi; Marcos Salganicoff; Arun Krishnan

doi:10.1117/12.770847

17 March 2008 Reduction of lymph tissue false positives in pulmonary embolism detection

Bernard Ghanem, Jianming Liang, Jinbo Bi, Marcos Salganicoff, Arun Krishnan

Proceedings Volume 6915, Medical Imaging 2008: Computer-Aided Diagnosis; 69151C (2008) https://doi.org/10.1117/12.770847
Event: Medical Imaging, 2008, San Diego, California, United States

Abstract

Pulmonary embolism (PE) is a serious medical condition, characterized by the partial/complete blockage of an artery within the lungs. We have previously developed a fast yet effective approach for computer aided detection of PE in computed topographic pulmonary angiography (CTPA),¹ which is capable of detecting both acute and chronic PEs, achieving a benchmark performance of 78% sensitivity at 4 false positives (FPs) per volume. By reviewing the FPs generated by this system, we found the most dominant type of FP, roughly one third of all FPs, to be lymph/connective tissue. In this paper, we propose a novel approach that specifically aims at reducing this FP type. Our idea is to explicitly exploit the anatomical context configuration of PE and lymph tissue in the lungs: a lymph FP connects to the airway and is located outside the artery, while a true PE should not connect to the airway and must be inside the artery. To realize this idea, given a detected candidate (i.e. a cluster of suspicious voxels), we compute a set of contextual features, including its distance to the airway based on local distance transform and its relative position to the artery based on fast tensor voting and Hessian "vesselness" scores. Our tests on unseen cases show that these features can reduce the lymph FPs by 59%, while improving the overall sensitivity by 3.4%.

Citation Download Citation

Bernard Ghanem, Jianming Liang, Jinbo Bi, Marcos Salganicoff, and Arun Krishnan "Reduction of lymph tissue false positives in pulmonary embolism detection", Proc. SPIE 6915, Medical Imaging 2008: Computer-Aided Diagnosis, 69151C (17 March 2008); https://doi.org/10.1117/12.770847

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